The Challenge
A growing healthcare network struggling with diagnostic bottlenecks
A Regional Healthcare Network operating 3 hospitals with 500+ beds across the USA was facing critical challenges in their radiology department. With over 2,000 X-ray and CT scans arriving daily, their team of radiologists was overwhelmed, leading to diagnostic delays that directly impacted patient outcomes.
Patients were waiting 48-72 hours for diagnostic results, creating bottlenecks in treatment planning and increasing the risk of missed findings. The hospital needed a solution that could dramatically accelerate the diagnostic process while maintaining or improving accuracy.
Our AI Solution
Custom computer vision system for automated lung nodule detection
Deep Learning Model
Built a custom deep learning pipeline using PyTorch with ResNet-50 architecture, fine-tuned on 50,000+ annotated medical images for lung nodule detection and classification.
- ResNet-50 backbone with custom classification head
- Fine-tuned on 50,000+ annotated medical images
- Multi-class detection: benign, malignant, indeterminate
- Confidence scoring for every prediction
Real-Time Processing
Optimized inference pipeline processes each scan in 30 seconds, providing near-instant results to radiologists with highlighted regions of interest.
- 30-second processing per scan
- Automated region-of-interest highlighting
- Batch processing for overnight scans
- Priority queue for urgent cases
PACS Integration
Seamlessly integrated with the hospital's existing PACS (Picture Archiving and Communication System) via DICOM standards, requiring no workflow changes.
- Native DICOM protocol support
- Automatic scan ingestion from PACS
- Results embedded in radiology workflow
- Zero disruption to existing processes
HIPAA Compliance
Full HIPAA compliance with end-to-end encryption, audit logging, and de-identification capabilities for patient data protection.
- End-to-end AES-256 encryption
- Complete audit trail logging
- PHI de-identification pipeline
- Role-based access control
Results & Impact
Measurable improvements across every key metric
Technology Stack
Production-grade AI infrastructure built for healthcare
Deep Learning
PyTorch, ResNet-50, MONAI
API & Backend
FastAPI, Python, Docker
Cloud Infrastructure
AWS GPU Instances, S3, ECR
Compliance
HIPAA, DICOM, HL7 FHIR
"Bytesar's AI system has transformed our radiology department. We're now able to process scans 6x faster while maintaining-and even improving-diagnostic accuracy. This was one of the best technology investments we've made."
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